In cooperative relays networks, nodes cooperate with each other while transmitting packets. Cooperative networks can provide significant gains in overall throughput and energy efficiency. Using nodes with single antennas, cooperative communication exploits, in a distributed manner, an inherent spatial diversity in the network, which has different channels between different nodes. This minimizes the effects of fading, and at the same time reduces energy consumption of the network.
Cooperative strategies for relay networks with simple two-hop or three-hop topologies are described by R. Madan, N. B. Mehta, A. F. Molisch, and J. Zhang, “Energy efficient cooperative relaying over fading channels with simple relay selection,” Globecom 2006.
However, many cooperative relay networks have tens or even hundreds of nodes. In such networks, the topology is arbitrary. The network includes numerous decode-and-forward (relay) nodes that are powered by batteries. Therefore, energy efficiency is of critical importance.
At the same time, despite the presence of fading, the outage probability on a route from a source node to a destination node must be kept below a specified level to ensure reliability.
A key problem in cooperative networks with many nodes is finding an optimum route. This problem is significantly different from the traditional routing problem for networks. In traditional, non-cooperative routing, a packet is transmitted serially from the source node to the destination node, via a sequence of relay nodes that form a single route. Each relay node communicates only with two other nodes, i.e., the previous node and the next nodes along the route. Traditional networks do not transfer a packet along two different routes to a destination.
In cooperative routing, a set of relay nodes can cooperate to forward a packet in parallel along multiple routes. This requires that nodes communicate with more than two nodes, either multiple previous nodes or multiple next nodes. Each transmission along a cooperative route can be a broadcast from one previous node to multiple next nodes, or a cooperative transmission from multiple previous nodes relay nodes to a single next node using beamforming. Beamforming controls the phase and power of transmitted signals from multiple nodes so that the signals are received coherently at the next nodes.
The general problem of determining cooperative routes in relay networks with arbitrary network topologies is computationally hard. It involves determining which nodes participate in a cooperative route, the cost of acquiring channel state information (CSI), and the respective transmission power costs as a function of CSI, with a goal of minimizing the total energy consumption in the network, while retaining a certain quality of service (outage probability). For quasi-static channels, this general problem is known be NP-hard.
The modes of collaboration depends critically on channel state information (CSI) that is available at the relay nodes. If the relay nodes do not have CSI for the channels on which the relays transmit, collaborative space-time coding can be used to increase the diversity order, and thus reduce sensitivity to fading.
It is also helpful to distinguish between operation in quasi-static and time-varying fast-fading channels. In the quasi-static case, the channels do not change over a relatively long time, and the optimum collaborative route stays optimum for many consecutive packets. Thus, the relative cost for obtaining and communicating the CSI is negligible. For fast-fading channels, on the other hand, the channel gain of the channels can change from one transmission interval to the next. Thus, the CSI may need to be refreshed for each transmitted packet. The significant cost for this process has to be added to the total energy cost. It is desired minimize the cost while finding an optimal route in a cooperative relay network.
For quasi-static channels, the problem of finding an optimal cooperative route, with broadcasting and beamforming nodes, is known to be NP-hard. However, conventional networks generally do not exploit the broadcast nature of the channel after the first transmission, and are provably suboptimal for topologies that have multiple relays available in intermediate hops. While those heuristics can be extended to fast fading channels, a significant amount of CSI is needed at a number of consecutive hops on a route. Obtaining such CSI can entail a significant energy cost and complexity.
Cooperative routing in a network with fast fading channels and using a limited class of routing schemes over a specific network topology is described by A. Wittneben, I. Hammerstroem, and M. Kuhn, “Joint cooperative diversity and scheduling in low mobility wireless networks,” IEEE Global Telecommunications Conference (GLOBECOM), vol. 2, pp. 780-784, 2004. There, the cost of acquiring the CSI at the transmitting nodes is not considered. They assume relatively static channels, where the channel coherence time is much longer than the block transmission time. Their heuristics are not decentralized. In summary, they formulated the problem of finding the minimum energy cooperative route for a wireless network under idealized channel and receiver models. In practical applications, their assumptions are unreasonable because channels are anything but ideal.
It is desired to dynamically find optimal routes in a decentralized manner. It also is desired to consider large networks with cooperative routing exploiting various transmission modes.